Why hospitals adopt patient engagement functionalities at different speeds? A moderated trend analysis

Asagbra, O. Elijah; Burke, Darrell; Liang, Huigang

doi:10.1016/j.ijmedinf.2017.12.023

Cited by 17 publications

(25 citation statements)

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“…Previous research shows that organization characteristics such as hospital size, system membership, ownership, and teaching status are important to understanding the propensity to technology adoption. 4,23 Hospital size (small: 0-99 beds, medium: 100-399 beds, large: 400+ beds) is an accepted factor in predicting organizational capacity. 24 Thus, hospital characteristics that were included in the study based on past research contribution were hospital size (small: 0-99 beds, medium: 100-399 beds, large: 400+ beds), hospital ownership (for-profit, not-for-profit, and nonfederal government), teaching affiliation (major teaching, minor teaching, and nonteaching), hospital location (rural and urban), critical access hospital, part of a system, and part of a network.…”

Section: Methodsmentioning

confidence: 99%

Telehealth: Advances in Alternative Payment Models

Zhao

Hamadi

Haley

et al. 2020

Telemedicine and e-Health

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Introduction: The hospital sector has shifted its focus to advanced information and communication technologies to facilitate health care delivery through telehealth services to alleviate the industry's most pressing challenges in quality care and access, especially under changing reimbursement payment approaches. The aim of this study was to examine the association between alternative payment models (APMs), market competition, and telehealth provisions in the hospital setting. Materials and Methods: A secondary cross-sectional design to analyze 2018 census data of nonfederal short-term acute care hospitals in the United States was used. Multilevel logistic regressions models were used to analyze data from 4,257 hospitals across 1,874 counties. Counties with less than one hospital were excluded. Results: Regarding APMs, we found that hospital participation in accountable care organizations and participation in a bundled payment risk arrangement are significantly associated with the provision of telehealth services. From the market perspective, competitive advantage was found to be statistically associated with hospitals providing telehealth services. In addition, other hospital characteristics such as ownership, part of a system, part of a network, and major teaching affiliation also have impact on the provision of telehealth. Conclusions: The increase uptake of telehealth-related capabilities and their strong integration into care-delivery systems under APMs present exciting opportunities to enhance the merit of clinical care, and challenges as clinical professionals are not adept to using such technologies. There is a need to provide comprehensive of evidence on telehealth.

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Section: Methodsmentioning

confidence: 99%

Telehealth: Advances in Alternative Payment Models

Zhao

Hamadi

Haley

et al. 2020

Telemedicine and e-Health

View full text Add to dashboard Cite

show abstract

“…Within the general field of organizational technology adoption, Tornatzky and Fleischer [ 17 ] developed the TOE framework, which is a generic framework that comprehensively covers potential areas of relevant influence on organizational technology adoption structured by 3 different contexts: a technological context, an organizational context, and an environmental context [ 22 ]. The TOE framework has been extensively applied to study hospitals’ adoption of various information technologies [ 23 - 25 ]. A strength (and weakness) of the TOE framework is its general applicability [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

“…The organizational context of the TOE framework refers to the organizations’ internal structures and processes that may facilitate or constrain the adoption of new information technology [ 18 , 46 ]. One basic organizational factor included in many TOE studies on the adoption of technology in hospitals is the hospital size [ 23 , 24 , 47 , 48 ]. The findings of these studies are mainly similar, showing that larger hospitals adopt new technologies faster.…”

Section: Introductionmentioning

confidence: 99%

“…On the one hand, hospital size is seen as an indicator of the extent of internal infrastructure. In this regard, a certain size means that a hospital has all necessary resources and capabilities as well as the ability to set up additional assets to apply new technology adequately [ 23 , 24 , 48 ]. On the other hand, hospital size is seen as an indicator for the operational volume of patients served by the hospital [ 47 , 49 , 50 ].…”

Section: Introductionmentioning

confidence: 99%

“…In this regard, the hospitals’ decision to adopt new information technology can be influenced by their association with a parent group or hospital network (eg, Hirslanden or the Swiss Medical Network in Switzerland). Such groups are seen as effective communicators and facilitators of innovations for their member hospitals, and they often provide technological support and shared services to implement new technologies [ 23 ]. Similarly, exploratory studies have shown that hospitals that are affiliated with a health or hospital system are more likely to be present on social media [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

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Technological, Organizational, and Environmental Factors Influencing Social Media Adoption by Hospitals in Switzerland: Cross-Sectional Study

Beier¹,

Früh²

2020

J Med Internet Res

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Background Social media platforms are important tools for hospitals. These platforms offer many potential benefits in various areas of application for hospitals to connect and interact with their stakeholders. However, hospitals differ immensely in their social media adoption. There are studies that provide initial findings on individual factors influencing social media adoption by hospitals, but there is no comprehensive and integrated model. Objective This study aimed to develop a comprehensive model of social media adoption by hospitals in the context of the Swiss health care system and to test the model with empirical data from Switzerland. Methods To develop our model, we applied the general technology-organization-environment framework of organizational technology adoption and adapted it to the specific context of social media adoption by hospitals in Switzerland. To test our model, we collected empirical data on all 283 hospitals in Switzerland and identified the accounts they operate on 7 different social media platforms (Facebook, Google+, Twitter, Instagram, LinkedIn, XING, and YouTube). We tested the hypotheses of our model by means of binary logistic regression (dependent variable: platform adoption) and negative binomial regression (dependent variable: number of different platforms adopted). Results Our general model on social media adoption received broad support. Overall, hospitals in Switzerland are more likely to adopt social media if they have a higher share of patients with voluntary health insurance or have a higher patient volume. In contrast, they are less likely to operate their own social media accounts if they are associated with a hospital network. However, some hypotheses of our model received only partial support for specific social media platforms; for instance, hospitals in Switzerland are more likely to adopt XING if they provide an educational program and are more likely to adopt LinkedIn if they are located in regions with higher competition intensity. Conclusions Our study provides a comprehensive model of social media adoption by hospitals in Switzerland. This model shows, in detail, the factors that influence hospitals in Switzerland in their social media adoption. In addition, it provides a basic framework that might be helpful in systematically developing and testing comprehensive models of social media adoption by hospitals in other countries.

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Acceptance of Simulated Adult Patients With Medicaid Insurance Seeking Care in a Cancer Hospital for a New Cancer Diagnosis

et al. 2022

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Key Points Question Can individuals insured by Medicaid access cancer care services at high-performing cancer-designated hospitals? Findings In this cross-sectional study of 334 facilities recognized for cancer care, 95.5% accepted new patients with Medicaid for breast cancer, 90.4% for colorectal cancer, 86.8% for kidney cancer, and 79.6% for skin cancer (melanoma) care. Medicaid was accepted for all 4 surveyed cancers at 67.7% of facilities. Meaning Despite increases in the number of US residents insured through Medicaid, these findings suggest that barriers to accessing cancer care exist at high-quality centers.

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Why hospitals adopt patient engagement functionalities at different speeds? A moderated trend analysis

Cited by 17 publications

References 50 publications

Telehealth: Advances in Alternative Payment Models

Telehealth: Advances in Alternative Payment Models

Technological, Organizational, and Environmental Factors Influencing Social Media Adoption by Hospitals in Switzerland: Cross-Sectional Study

Acceptance of Simulated Adult Patients With Medicaid Insurance Seeking Care in a Cancer Hospital for a New Cancer Diagnosis

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